Search (32 results, page 1 of 2)

  • × theme_ss:"Social tagging"
  1. Müller-Prove, M.: Modell und Anwendungsperspektive des Social Tagging (2008) 0.02 
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    Date
    21. 6.2009 9:55:29
    Pages
    S.15-22
  2. Niemann, C.: Tag-Science : Ein Analysemodell zur Nutzbarkeit von Tagging-Daten (2011) 0.02 
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    Date
    29. 5.2012 13:58:08
    29. 5.2012 14:15:36
    Source
    ¬Die Kraft der digitalen Unordnung: 32. Arbeits- und Fortbildungstagung der ASpB e. V., Sektion 5 im Deutschen Bibliotheksverband, 22.-25. September 2009 in der Universität Karlsruhe. Hrsg: Jadwiga Warmbrunn u.a
  3. Chen, M.; Liu, X.; Qin, J.: Semantic relation extraction from socially-generated tags : a methodology for metadata generation (2008) 0.01 
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    Date
    20. 2.2009 10:29:07
    Source
    Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas
  4. Xu, C.; Ma, B.; Chen, X.; Ma, F.: Social tagging in the scholarly world (2013) 0.01 
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    Abstract
    The number of research studies on social tagging has increased rapidly in the past years, but few of them highlight the characteristics and research trends in social tagging. A set of 862 academic documents relating to social tagging and published from 2005 to 2011 was thus examined using bibliometric analysis as well as the social network analysis technique. The results show that social tagging, as a research area, develops rapidly and attracts an increasing number of new entrants. There are no key authors, publication sources, or research groups that dominate the research domain of social tagging. Research on social tagging appears to focus mainly on the following three aspects: (a) components and functions of social tagging (e.g., tags, tagging objects, and tagging network), (b) taggers' behaviors and interface design, and (c) tags' organization and usage in social tagging. The trend suggest that more researchers turn to the latter two integrated with human computer interface and information retrieval, although the first aspect is the fundamental one in social tagging. Also, more studies relating to social tagging pay attention to multimedia tagging objects and not only text tagging. Previous research on social tagging was limited to a few subject domains such as information science and computer science. As an interdisciplinary research area, social tagging is anticipated to attract more researchers from different disciplines. More practical applications, especially in high-tech companies, is an encouraging research trend in social tagging.
  5. Antin, J.; Earp, M.: With a little help from my friends : self-interested and prosocial behavior on MySpace Music (2010) 0.01 
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    Abstract
    In this article, we explore the dynamics of prosocial and self-interested behavior among musicians on MySpace Music. MySpace Music is an important platform for social interactions and at the same time provides musicians with the opportunity for significant profit. We argue that these forces can be in tension with each other, encouraging musicians to make strategic choices about using MySpace to promote their own or others' rewards. We look for evidence of self-interested and prosocial friending strategies in the social network created by Top Friends links. We find strong evidence that individual preferences for prosocial and self-interested behavior influence friending strategies. Furthermore, our data illustrate a robust relationship between increased prominence and increased attention to others' rewards. These results shed light on how musicians manage their interactions in complex online environments and extend research on social values by demonstrating consistent preferences for prosocial or self-interested behavior in a multifaceted online setting.
  6. Wei, W.; Ram, S.: Utilizing sozial bookmarking tag space for Web content discovery : a social network analysis approach (2010) 0.01 
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    Abstract
    Social bookmarking has gained popularity since the advent of Web 2.0. Keywords known as tags are created to annotate web content, and the resulting tag space composed of the tags, the resources, and the users arises as a new platform for web content discovery. Useful and interesting web resources can be located through searching and browsing based on tags, as well as following the user-user connections formed in the social bookmarking community. However, the effectiveness of tag-based search is limited due to the lack of explicitly represented semantics in the tag space. In addition, social connections between users are underused for web content discovery because of the inadequate social functions. In this research, we propose a comprehensive framework to reorganize the flat tag space into a hierarchical faceted model. We also studied the structure and properties of various networks emerging from the tag space for the purpose of more efficient web content discovery. The major research approach used in this research is social network analysis (SNA), together with methodologies employed in design science research. The contribution of our research includes: (i) a faceted model to categorize social bookmarking tags; (ii) a relationship ontology to represent the semantics of relationships between tags; (iii) heuristics to reorganize the flat tag space into a hierarchical faceted model using analysis of tag-tag co-occurrence networks; (iv) an implemented prototype system as proof-of-concept to validate the feasibility of the reorganization approach; (v) a set of evaluations of the social functions of the current networking features of social bookmarking and a series of recommendations as to how to improve the social functions to facilitate web content discovery.
  7. Li, D.; Ding, Y.; Sugimoto, C.; He, B.; Tang, J.; Yan, E.; Lin, N.; Qin, Z.; Dong, T.: Modeling topic and community structure in social tagging : the TTR-LDA-Community model (2011) 0.01 
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    Abstract
    The presence of social networks in complex systems has made networks and community structure a focal point of study in many domains. Previous studies have focused on the structural emergence and growth of communities and on the topics displayed within the network. However, few scholars have closely examined the relationship between the thematic and structural properties of networks. Therefore, this article proposes the Tagger Tag Resource-Latent Dirichlet Allocation-Community model (TTR-LDA-Community model), which combines the Latent Dirichlet Allocation (LDA) model with the Girvan-Newman community detection algorithm through an inference mechanism. Using social tagging data from Delicious, this article demonstrates the clustering of active taggers into communities, the topic distributions within communities, and the ranking of taggers, tags, and resources within these communities. The data analysis evaluates patterns in community structure and topical affiliations diachronically. The article evaluates the effectiveness of community detection and the inference mechanism embedded in the model and finds that the TTR-LDA-Community model outperforms other traditional models in tag prediction. This has implications for scholars in domains interested in community detection, profiling, and recommender systems.
  8. Chae, G.; Park, J.; Park, J.; Yeo, W.S.; Shi, C.: Linking and clustering artworks using social tags : revitalizing crowd-sourced information on cultural collections (2016) 0.01 
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    Abstract
    Social tagging is one of the most popular methods for collecting crowd-sourced information in galleries, libraries, archives, and museums (GLAMs). However, when the number of social tags grows rapidly, using them becomes problematic and, as a result, they are often left as simply big data that cannot be used for practical purposes. To revitalize the use of this crowd-sourced information, we propose using social tags to link and cluster artworks based on an experimental study using an online collection at the Gyeonggi Museum of Modern Art (GMoMA). We view social tagging as a folksonomy, where artworks are classified by keywords of the crowd's various interpretations and one artwork can belong to several different categories simultaneously. To leverage this strength of social tags, we used a clustering method called "link communities" to detect overlapping communities in a network of artworks constructed by computing similarities between all artwork pairs. We used this framework to identify semantic relationships and clusters of similar artworks. By comparing the clustering results with curators' manual classification results, we demonstrated the potential of social tagging data for automatically clustering artworks in a way that reflects the dynamic perspectives of crowds.
  9. Kipp, M.E.; Beak, J.; Choi, I.: Motivations and intentions of flickr users in enriching flick records for Library of Congress photos (2017) 0.01 
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    Abstract
    The purpose of this study is to understand users' motivations and intentions in the use of institutional collections on social tagging sites. Previous social tagging studies have collected social tagging data and analyzed how tagging functions as a tool to organize and retrieve information. Many studies focused on the patterns of tagging rather than the users' perspectives. To provide a more comprehensive picture of users' social tagging activities in institutional collections, and how this compares to social tagging in a more personal context, we collected data from social tagging users by surveying 7,563 participants in the Library of Congress's Flickr Collection. We asked users to describe their motivations for activities within the LC Flickr Collection in their own words using open-ended questions. As a result, we identified 11 motivations using a bottom-up, open-coding approach: affective reactions, opinion on photo, interest in subject, contribution to description, knowledge sharing, improving findability, social network, appreciation, personal use, and personal relationship. Our study revealed that affective or emotional reactions play a critical role in the use of social tagging of institutional collections by comparing our findings to existing frameworks for tagging motivations. We also examined the relationships between participants' occupations and our 11 motivations.
  10. Peters, I.: Folksonomies und kollaborative Informationsdienste : eine Alternative zur Websuche? (2011) 0.01 
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    Pages
    S.29-53
  11. Evedove Tartarotti, R. Dal'; Lopes Fujita, M.: ¬The perspective of social indexing in online bibliographic catalogs : between the individual and the collaborative (2016) 0.01 
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    Source
    Knowledge organization for a sustainable world: challenges and perspectives for cultural, scientific, and technological sharing in a connected society : proceedings of the Fourteenth International ISKO Conference 27-29 September 2016, Rio de Janeiro, Brazil / organized by International Society for Knowledge Organization (ISKO), ISKO-Brazil, São Paulo State University ; edited by José Augusto Chaves Guimarães, Suellen Oliveira Milani, Vera Dodebei
  12. Catarino, M.E.; Baptista, A.A.: Relating folksonomies with Dublin Core (2008) 0.00 
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    Pages
    S.14-22
    Source
    Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas
  13. Marchitelli, A.; Piazzini, T.: OPAC, SOPAC e social networking : cataloghi di biblioteca 2.0? (2008) 0.00 
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    Date
    29. 1.1996 17:18:10
  14. Oudenaar, H.; Bullard, J.: NOT A BOOK : goodreads and the risks of social cataloging with insufficient direction (2024) 0.00 
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    Date
    22.11.2023 18:29:56
  15. Harrer, A.; Lohmann, S.: Potenziale von Tagging als partizipative Methode für Lehrportale und E-Learning-Kurse (2008) 0.00 
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    Date
    21. 6.2009 12:22:44
  16. Furner, J.: User tagging of library resources : toward a framework for system evaluation (2007) 0.00 
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    Date
    26.12.2011 13:29:31
  17. Corrado, E.; Moulaison, H.L.: Social tagging and communities of practice : two case studies (2008) 0.00 
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    Date
    27.12.2008 11:20:29
  18. Kruk, S.R.; Kruk, E.; Stankiewicz, K.: Evaluation of semantic and social technologies for digital libraries (2009) 0.00 
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  19. Rolla, P.J.: User tags versus Subject headings : can user-supplied data improve subject access to library collections? (2009) 0.00 
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  20. Strader, C.R.: Author-assigned keywords versus Library of Congress Subject Headings : implications for the cataloging of electronic theses and dissertations (2009) 0.00 
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Authors

Years

Languages

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  • d 4
  • i 1
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Types

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  • el 3
  • b 2
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Themes